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Titlebook: Applied Reconfigurable Computing; 13th International S Stephan Wong,Antonio Carlos Beck,Luigi Carro Conference proceedings 2017 Springer In

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發(fā)表于 2025-3-21 18:23:32 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Applied Reconfigurable Computing
期刊簡(jiǎn)稱13th International S
影響因子2023Stephan Wong,Antonio Carlos Beck,Luigi Carro
視頻videohttp://file.papertrans.cn/161/160093/160093.mp4
發(fā)行地址Includes supplementary material:
學(xué)科分類Lecture Notes in Computer Science
圖書封面Titlebook: Applied Reconfigurable Computing; 13th International S Stephan Wong,Antonio Carlos Beck,Luigi Carro Conference proceedings 2017 Springer In
影響因子This book constitutes the refereed proceedings of the 13th International?Symposium on Applied Reconfigurable Computing, ARC 2017, held in Delft, The Netherlands, in April 2017..The 17 full papers and 11 short papers presented in this volume were carefully reviewed and?selected from 49 submissions. They are organized in topical sections on adaptive architectures, embedded computing and security, simulation and synthesis, design space exploration, fault tolerance, FGPA-based designs, neural neworks, and languages and estimation techniques..
Pindex Conference proceedings 2017
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板凳
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https://doi.org/10.1007/978-1-4020-8913-8an architecture targeting real-time embedded image and video processing, which combines runtime reconfigurable processing, low-latency and high performance. Being a configurable architecture allows the combination of powerful video processing operators (Processing Elements or PEs) to build the targe
地板
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Eco-Efficiency in Industry and Sciencesimulation results, large sets of workloads need to be evaluated. In this work, we present a neural in-memory simulator capable of executing deep learning applications inside 3D-stacked memories. With the reduction of data movement and by including a simple accelerator layer near to memory, our syst
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發(fā)表于 2025-3-22 11:00:56 | 只看該作者
Zygfryd A. Nowak,Michal J. Cichyhat is designed to stream data between intermediate stages of an image processing pipeline. These pipelines are commonplace in medical applications such as X-ray imagers. By using a streaming memory hierarchy, performance is increased by a factor that depends on the number of stages (. when using 4
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發(fā)表于 2025-3-22 15:33:46 | 只看該作者
https://doi.org/10.1007/978-1-4020-8913-8ey are activated, the goal is to avoid cumbersome and sometimes destructive pre-fabrication and pre-deployment tests for Trojans in SoCs, by building systems capable of capturing Trojan activation or simply nullifying their effect at run-time to prevent damage to the system. To reach this goal, non-
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https://doi.org/10.1007/978-94-010-0197-7 Verilog and VHDL are widely used to design FPGA accelerators, however, they require significant expertise and considerable design efforts. Recent advances in high-level synthesis have brought forward tools that relieve the burden of FPGA application development but the achieved performance results
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https://doi.org/10.1007/978-94-010-0197-7ring system development, hardware implementations require particular attention to take full advantage of performance gains through parallelization when using hashes. For many use cases, such as hash tables or Bloom filters, several independent short hash values for the same input key are needed. Her
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https://doi.org/10.1007/978-94-010-0197-7ed as hard cores (ASIC) or soft cores (RTL). Soft reconfigurable cores outperform hard reconfigurable cores by preserving the ASIC synthesis flow, at the cost of lowering scalability but also exacerbating timing closure issues. This article tackles these two issues and introduces the ARGen generator
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